Examining the effects of sustained cannabis abstinence on affective symptoms in people with cannabis use disorder
Bibliographic record
Abstract
Introduction: Cannabis is often used to cope with affective symptoms, such as depression or anxiety. In Canada, 43% of people who used cannabis in 2023 perceived that cannabis use was beneficial to their mental health, while only 8% thought that it was harmful. Paradoxically, longitudinal studies suggest that cannabis use is associated with the development and maintenance of affective symptoms. It is therefore crucial to understand if cannabis abstinence benefits affective symptoms. Previous studies found that depressive and anxiety symptoms improved with 28 days of cannabis abstinence. However, most of these studies included participants with psychiatric/medical comorbidities or were conducted in adolescents. Studies that did include participants without comorbidities failed to include an adequate control group. Therefore, to determine if these findings extend to adults without comorbidities, we aimed to investigate the effects of 28 days of cannabis abstinence on depressive and anxiety symptoms in adults with cannabis use disorder (CUD) with no comorbidities using an appropriate control group. Given that previous research did not assess the effect of sex on changes in affective symptoms, our exploratory aim was to compare the trajectory of depressive and anxiety symptoms during 28 days of cannabis abstinence between males and females.Methods: We recruited adults (N=25; 18-55 years old) with CUD, a positive cannabis urine toxicology, and no current DSM-5 disorders (other than CUD) or medical comorbidities. Participants were randomized using a 3:2 ratio to a cannabis abstinence arm (AB, n=16) or a non-abstinent (cannabis-as-usual control) arm (NA, n=9), respectively. Depressive symptoms were assessed weekly with the Hamilton-Depression Rating Scale. Anxiety was assessed weekly using the state subscale of the State Trait Anxiety Inventory. Cannabis abstinence was determined with the Timeline Follow Back, a self-report interview, and was encouraged using contingency management and weekly behavioural support.Results: Fourteen of the 16 participants (88%) in AB self-reported 28 days of cannabis abstinence. Relative to NA, depressive (F(4,84)=1.83, p=.15) and anxiety (F(4, 84)=.79, p=.47) symptoms did not significantly change during abstinence in AB. Further, the effect of sex on the trajectory of depressive (F(4, 36)=0.22, p=.93) and anxiety (F(4, 48=.46, p=.60) symptoms was not significant. Due to the study being underpowered, we also outlined the general pattern observed in the data. Among AB depressive symptoms increased from baseline to day 7, peaked at day 7, and then returned to baseline levels by day 28. Additionally, when parsed according to sex, females experienced a greater increase in depressive symptoms from baseline to day 7 than males. Conversely, anxiety symptoms decreased from baseline to day 28 in both AB and NA, and no sex differences were observed in anxiety symptoms.Conclusion: In this preliminary study, severity of depressive, but not anxiety, symptoms increased from baseline to 7 days before returning to baseline levels by day 28 in people with CUD who underwent 28 days of cannabis abstinence. The peak in depressive symptoms at day 7 may reflect transient cannabis withdrawal effects. Further, females experienced a greater increase in depressive symptoms than males during the first week of cannabis abstinence, suggesting that females may be more vulnerable to relapse during the first week of cannabis abstinence. Importantly, our findings indicate that affective symptoms do not get worse after 28 days of cannabis abstinence which provides evidence that cannabis use does not benefit or improve affective symptoms. Future studies should biochemically verify self-reported cannabis abstinence and include larger samples
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".